Cao et al. (2019, https://doi.org/10.1029/2018WR023568) proposed a modified particle filter‐based data assimilation method with a local weighting procedure (MPFDA‐LW) for a two‐dimensional hydrodynamic model (HydroM2D) in dam‐break flood simulation. The MPFDA‐LW method intends to take into account the spatial‐temporal variability of the Manning coefficient to improve the performances of the HydroM2D model. Although Cao et al. (2019, https://doi.org/10.1029/2018WR023568) correctly pointed out that the Manning coefficient may spatially and temporally vary during a flooding process, the approach they handled this issue was inappropriate because they arbitrarily adjusted model parameters without considering the physical mechanism behind them. In addition, contrary to what the authors claimed, the proposed MPFDA‐LW method can barely improve the prediction of flooding processes, because changing the Manning coefficient at several computational grid cells has little influence on the overall flooding processes.

中文翻译：

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Cao等人对“考虑了粗糙度时空变化的高精度二维流体力学模型的改进的基于粒子滤波的数据同化方法：模拟溃坝洪水泛滥”的评论。

曹等。（2019，https://doi.org/10.1029/2018WR023568）针对大坝洪水中的二维水动力模型（HydroM2D），提出了一种基于局部加权程序（MPFDA‐LW）的改进的基于粒子过滤器的数据同化方法模拟。MPFDA-LW方法旨在考虑曼宁系数的时空变化，以改善HydroM2D模型的性能。虽然曹等。（2019，https://doi.org/10.1029/2018WR023568）正确地指出曼宁系数在洪水过程中可能在空间和时间上变化，他们处理此问题的方法是不合适的，因为他们随意调整模型参数而不考虑物理他们背后的机制。此外，与作者的主张相反，